class_docstr: Power variance function:
  
  V(mu) = fabs(mu)**power
  
  INPUTS:
     power -- exponent used in power variance function
docstr: Power variance function
  
  INPUTS:
     mu  -- mean parameters
  
  OUTPUTS: v
     v   -- fabs(mu)**self.power
docstr_tok: ["Power","variance","function","INPUTS",":","mu","--","mean","parameters","OUTPUTS",":","v","v","--","fabs","(","mu",")","*","*","self.power"]
code: def __call__(self, mu):
      """
      Power variance function
  
      INPUTS:
         mu  -- mean parameters
  
      OUTPUTS: v
         v   -- fabs(mu)**self.power
      """
      return np.power(np.fabs(mu), self.power)
  
file_path: nipy/nipy/algorithms/statistics/models/family/varfuncs.py
imports: import numpy
label_desc: Use image node_id 2 for calling the Power obj's underlying member method code with example usage: obj.__call__(mu) and returns: np